Abstract
Associating genes with diseases is an active area of research because it is useful for helping human health with applications to clinical diagnosis and therapy. This paper proposes two methods to guide the associations between genes and diseases: (1) making use of the proximity relationship between genes and diseases and (2) utilizing GO terms shared by genes and diseases for similarity comparison. The experiments show that associations utilizing GO terms perform better than using word proximity. The results reveal that the GO terms act as a good gene-disease association feature.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011 |
| Pages | 1748-1752 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2011 |
| Event | 2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011 - Shanghai, China Duration: 2011 Oct 15 → 2011 Oct 17 |
Publication series
| Name | Proceedings - 2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011 |
|---|---|
| Volume | 4 |
Other
| Other | 2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011 |
|---|---|
| Country/Territory | China |
| City | Shanghai |
| Period | 2011/10/15 → 2011/10/17 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Gene Ontology
- bioinformatics
- gene-disease association
- text mining
- word proximity relationship
ASJC Scopus subject areas
- Biomedical Engineering
- Health Informatics
- Health Information Management
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